Non-linear auto-regressive models for cross-frequency coupling in neural time series T Dupré la Tour, L Tallot, L Grabot, V Doyère, V Van Wassenhove, ... PLoS computational biology 13 (12), e1005893, 2017 | 63* | 2017 |
Learning the morphology of brain signals using alpha-stable convolutional sparse coding M Jas*, T Dupré la Tour*, U Simsekli, A Gramfort Advances in Neural Information Processing Systems (NeurIPS), 1099-1108, 2017 | 56 | 2017 |
Multivariate convolutional sparse coding for electromagnetic brain signals T Dupré la Tour*, T Moreau*, M Jas, A Gramfort Advances in Neural Information Processing Systems (NeurIPS), 3292-3302, 2018 | 54 | 2018 |
Feature-space selection with banded ridge regression T Dupré la Tour, M Eickenberg, A Nunez-Elizalde, JL Gallant NeuroImage 264, 119728, 2022 | 36 | 2022 |
The strength of alpha-beta oscillatory coupling predicts motor timing precision L Grabot, TW Kononowicz, T Dupré la Tour, A Gramfort, V Doyère, ... Journal of Neuroscience, 2473-18, 2019 | 27 | 2019 |
Benchopt: Reproducible, efficient and collaborative optimization benchmarks T Moreau, M Massias, A Gramfort, P Ablin, PA Charlier, M Dagréou, ... Advances in Neural Information Processing Systems (NeurIPS), 2022 | 25 | 2022 |
scikit-learn/scikit-learn: Scikit-learn 0.22. 1 O Grisel, A Mueller, A Gramfort, G Louppe, P Prettenhofer, M Blondel, ... Zenodo, 2020 | 15 | 2020 |
Semantic representations during language comprehension are affected by context F Deniz, C Tseng, L Wehbe, T Dupré la Tour, JL Gallant Journal of Neuroscience, 2023 | 14 | 2023 |
A finer mapping of convolutional neural network layers to the visual cortex T Dupré la Tour, M Lu, M Eickenberg, JL Gallant Advances in Neural Information Processing Systems (NeurIPS), SVRHM Workshop, 2021 | 8* | 2021 |
scikit-learn-contrib/skope-rules v1. 0.1 N Goix, V Birodkar, F Gardin, J Schertzer, H Jeong, M Kumar, A Gramfort, ... Preprint at https://doi. org/10.5281/zenodo 4316671 (1), 2020 | 5 | 2020 |
Non-linear models for neurophysiological time series T Dupré la Tour Université Paris-Saclay, 2018 | 5* | 2018 |
The cortical representation of language timescales is shared between reading and listening C Chen, T Dupré la Tour, J Gallant, D Klein, F Deniz Communications Biology, 2024 | 4* | 2024 |
Gallant Lab Natural Short Clips 3T fMRI Data AG Huth, S Nishimoto, AT Vu, T Dupré la Tour, JL Gallant | 4 | 2022 |
Parametric estimation of spectrum driven by an exogenous signal T Dupré la Tour, Y Grenier, A Gramfort 42nd IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 4 | 2017 |
scikit-learn/scikit-learn: Scikit-learn 1.3. 1 O Grisel, A Mueller, A Gramfort, G Louppe, TJ Fan, P Prettenhofer, ... Zenodo, 2022 | 3 | 2022 |
Driver estimation in non-linear autoregressive models T Dupré la Tour, Y Grenier, A Gramfort 43nd IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 3 | 2018 |
The Voxelwise Modeling framework: a tutorial introduction to fitting encoding models to fMRI data T Dupré la Tour, M Visconti di Oleggio Castello, JL Gallant PsyArxiv, 2024 | | 2024 |
Model connectivity: leveraging the power of encoding models to overcome the limitations of functional connectivity EX Meschke, M Visconti di Oleggio Castello, T Dupre la Tour, JL Gallant bioRxiv, 2023.07. 17.549356, 2023 | | 2023 |
Dynamic, naturalistic faces embedded in a narrative elicit responses in the distributed face processing system V Chauhan, R Philip, MV di Oleggio Castello, G Jiahui, M Feilong, ... Journal of Vision 22 (14), 4386-4386, 2022 | | 2022 |
Long-term recordings from area V4 neurons and an accurately-predicting deep convolutional energy model reveal spatial, chromatic and temporal tuning properties under … M Winter*, T Dupré la Tour*, M Eickenberg*, M Oliver*, J Gallant Journal of Vision 22 (14), 4363-4363, 2022 | | 2022 |